Estimation of Spatial Groundwater Recharge Using WetSpass Model for East Wasit Province, Iraq

H. Al-Badry, Mohammed S. Shamkhi
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引用次数: 1

Abstract

AbstractGroundwater is an important water source, especially in arid and semi-arid areas. Recharge is critical to managing and analyzing groundwater resources despite estimation difficulty due to temporal and spatial change. The study aim is to estimate annual groundwater recharge for the eastern Wasit Province part, Iraq. Where suffers from a surface water shortage due to the region's high elevation above Tigris River water elevation by about 60 m, it is necessary to search for alternative water sources, such as groundwater use. The spatially distributed WetSpass model was used to estimate the annual recharge. The inputs for the model were prepared using the ARC-GIS program, which includes the topography and slope grid, soil texture grid, land use, groundwater level grid, and meteorological data grids for the study area for the period (2014-2019). The result shows that the annual recharge calculated using the WetSpass model (2014-2019) varied of 0 to 65.176 mm/year at an average of 27.117 mm/year, about 10.8%, while the rate of the surface runoff was 5.2% and Evapotranspiration formed 83.33% of the annual rainfall rate of 251.192 mm. The simulation results reveal that the WetSpass model simulates the components of the hydrological water budget correctly. For managing and planning available water resources, a best grasp of the simulation of long-range average geographical distribution around the water balance components is beneficial.
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利用WetSpass模型估算伊拉克东Wasit省地下水空间补给
摘要地下水是重要的水源,特别是在干旱半干旱地区。补给对地下水资源的管理和分析至关重要,尽管由于时空变化的原因,补给的估算存在困难。这项研究的目的是估计伊拉克东部瓦西特省地区每年的地下水补给。由于该地区海拔高于底格里斯河约60米,地表水短缺,有必要寻找替代水源,如地下水的使用。利用空间分布的wespass模型估算年补给量。模型的输入使用ARC-GIS程序,包括研究区2014-2019年期间的地形和坡度网格、土壤质地网格、土地利用、地下水位网格和气象数据网格。结果表明:2014-2019年,利用wespass模型计算的年补给量在0 ~ 65.176 mm/年之间变化,平均为27.117 mm/年,约为10.8%,地表径流量为5.2%,蒸散发占年降雨量251.192 mm的83.33%。模拟结果表明,WetSpass模型能较好地模拟水文水收支各组成部分。为了管理和规划可用水资源,最好地掌握水平衡成分周围长期平均地理分布的模拟是有益的。
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